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Smart freeway is the newest form of next generation of freeway system which aims to achieve more sustainable objectives utilizing advanced information and communication technologies. Taking the advantages of digital twin on near‐real‐time interaction between the physical and cyber systems, the framework, operation, and enabled technologies of digital twin smart freeway (DTSF) are developed in this paper. A three‐layer conceptual framework is first discussed for understanding the fundamental structure, core components, and operation procedure of a DTSF system in the context of smart transportation. The key technologies of a DTSF system are also investigated, such as simulation modelling, big data analysis, intelligent prediction, and integrated freeway control. Moreover, a well‐designed case study based on Simulation of Urban Mobility (SUMO) is provided to verify the efficiency of the proposed freeway control strategy by integrating perimeter control of upstream urban network and traffic regulation of freeway segments. To the best of our knowledge, it is the first time to investigate integrated freeway control under the framework of digital twin. [ABSTRACT FROM AUTHOR]

• Digital twins-based flexible operating of open architecture production line. • The reconfigurability based on open architectural architecting of cyber system and physical system. • Integration of online system-level logistics simulation and equipment-level multi-physical field simulation. Individualized manufacturing implies high flexibility of both the hardware and software of the production lines based on a fast physical and logical system (de)commissioning. This paper proposes an open architecture production line (OAPL) design together with a digital twins-based flexible operating approach for individualized manufacturing. Firstly, an OAPL is designed and implemented with physical reconfigurability by orchestrating different open architectural platforms together with open architecture machine tools (OAMTs). Secondly, an open architectural style modeling and configuration method is presented to enable the software reconfigurability of the controls of the OAPL. Thirdly, a digital twin-based online process emulating and multi-physics simulation is integrated to aid the comprehensive characterizing of the operation status of the OAPL. Based on the system reconfigurability and digital twins system, a triple-layer Learning-Optimization-Reacting approach together with an ensemble algorithm for flexible operating of the OAPL is proposed. The digital twins are formed with the ability to flexibly operate the OAPL for catering to different individualized requirements. A demonstrative implementation of a stepping-motor assembly OAPL is presented finally. [ABSTRACT FROM AUTHOR]

The COVID-19 has become a global pandemic that dramatically impacted human lives and economic activities. Due to the high risk of getting affected in high-density population areas and the implementation of national emergency measures under the COVID-19 pandemic, both travel and transportation among cities become difficult for engineers and equipment. Consequently, the costly physical commissioning of a new manufacturing system is greatly hindered. As an emerging technology, digital twins can achieve semi-physical simulation to avoid the vast cost of physical commissioning of the manufacturing system. Therefore, this paper proposes a digital twins-based remote semi-physical commissioning (DT-RSPC) approach for open architecture flow-type smart manufacturing systems. A digital twin system is developed to enable the remote semi-physical commissioning. The proposed approach is validated through a case study of digital twins-based remote semi-physical commissioning of a smartphone assembly line. The results showed that combining the open architecture design paradigm with the proposed digital twins-based approach makes the commissioning of a new flow-type smart manufacturing system more sustainable. [ABSTRACT FROM AUTHOR]

The energy-saving potential of original equipment manufacturers (OEMs) for electronic products is substantial owing to the huge market size of assembling industry in China. A semi-automatic electronic assembly line (SAEAL) for smart-phones is introduced, and its digital twin (DT) enabled energy-saving platform is developed as the hardware foundation. We propose a stochastic dynamics model via max-plus algebra to characterize the spatio-temporal nature of state transition, which provides dynamical opportunity windows for further energy-saving control strategy. Accordingly, model linearization is conducted to obtain linear state and output equations. Then, a model predictive control (MPC) approach for energy saving optimization is provided to determine the optimal start-stop control signal. The dynamics modeling and MPC approach have been applied and verified in the case of assembly line. The results show that the optimization approach could reach a proportion of 49% for the equipment sleep time of total running time and save a considerable amount of energy for normal production of OEMs. [Display omitted] • A digital twin prototype system of smart-phone assembly line is developed as the testing platform for energy-saving control. • The assembling behaviors of assembly line are depicted by linear state equations via max-plus semiring algebra. • A spatio-temporal dynamics model is provided to evaluate the system performance based on max-plus semiring algebra. • An energy-saving MPC approach is proposed to determine the start-stop control sequences of automatic machines. • The equipment's sleeping time can reach a proportion of 49% of total running time without production efficiency loss. [ABSTRACT FROM AUTHOR]